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Observational cohort study involving individuals of both sexes with a history of smoking, residing in municipalities in the state of Bahia and attended by the mobile unit, with the aim of evaluating the integration of artificial intelligence (AI) in the detection of pulmonary nodules and the prediction of ASCT in high-risk individuals undergoing CT screening.
Full description
The main objective of the study is compare the performance of a Sybil AI tool with the LungRADS classifications assigned by radiologists for the risk stratification of pulmonary nodules. Furthermore, it aims to assess the correlation between the AI-predicted STAS and histopathological confirmation, alongside imaging and AI results. The hypothesis is that the Sybil AI model will demonstrate comparable predictive accuracy and that the features predicted by the AI will correlate with the presence of STAS.
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Inclusion criteria
Individuals of both sexes, smokers or former smokers for a maximum of 15 years;
Exclusion criteria
Individuals who are unable to undergo a CT scan;
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AstraZeneca Clinical Study Information Center
Data sourced from clinicaltrials.gov
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